Metrics assessment system for health, fitness and lifestyle behavioral management

ABSTRACT

A software and hardware system is described that enables effective lifestyle management by providing a dynamic assessment of a user&#39;s physical and behavioral metrics via a high feedback ratio interface.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to health, fitness, andlifestyle management, and more specifically to a software and hardwaresystem which enables effective lifestyle management by providing adynamic assessment of a user's physical and behavioral metrics via ahigh feedback ratio interface.

2. Description of the Related Art

In the U.S., diet, exercise and personal health improvement marketsexceed $60 billion annually; yet, two thirds of adults are overweight.Links between obesity and numerous serious and fatal health conditionsare well documented. Lost worker productivity and increased health carecosts in America due to obesity exceed $100 billion annually. Beingobese is unhealthy, expensive and diminishes one's quality of life.These sobering realities, as well as social and personal pressures,however, are apparently not effective enough drivers for most people toachieve a healthy weight. Obesity rates in America and around thedeveloped world continue to rise at an alarming pace. A schism existsbetween what people want, or even need, and what they achieve.

Although 95% of diets reportedly fail, the 5% who succeed at losingweight represent the entirety of the social, economic and physiologicaldemographic spectrum. What, then, is the primary reason for this schism?The key differentiator between those who succeed and fail is motivationand behavior management. Motivation fuels behavior and results followbehavior. The schism, then, is a failure of behavior management.

A well-known key to weight control is a daily caloric balance—consumeonly as many calories in a day as are burned. That simple equation,however, and corresponding behavior is simply unattainable for manypeople. Why? Because the effort-to-reward mechanism is ineffective fortoo many people.

Motivation is unsustainable in an ineffective effort-to-rewardmechanism. An effective effort-to-reward mechanism can sustainmotivation and enable effective behavior management. Effectiveeffort-to-reward mechanisms meet necessary thresholds and balance of thefollowing four criteria:

-   -   1. Temporal—a reward must be timely enough to the effort to be        an effective motivator. Optimally, the reward would occur during        the effort or immediately following.    -   2. Association—an effort and reward must be tangibly related to        one another to be an effective motivator. Optimally, the effort        and reward are viscerally related, an innately understood link.    -   3. Assimilation—a reward must have meaning and value to the        subject to be an effective motivator.    -   4. Ratio—a reward-to-effort ratio must meet a minimum threshold        to be an effective motivator. The higher the ratio of reward to        effort the more effective the motivation.

It is important to note that ‘necessary thresholds’ vary from person toperson. One size does not fit all. A system or method must be flexibleto allow individual discovery of their own effective motivationalthreshold. In a fully realized healthy lifestyle, ‘exercise’ and ‘eatingright’ become rewards themselves.

Existing methods or systems to heighten people's motivation and enablebehavior management to achieve health, fitness and lifestyle goalsinclude: weight-loss counseling, pre-prepared and portioned meals,peer-to-peer support groups, fitness groups and clubs, healthchallenges, hypnosis and many others. Many of these methods and systemshave been in existence for years, even decades, yet obesity rates havenearly doubled in the past thirty years. For many people, currentmethods and systems fail to satisfy all four requirements of aneffective effort-to-reward mechanism.

Most lifestyle goals cannot be achieved in a single action; they are aprocess, achieved over time. If the action and behavior itself is not areward mechanism for the individual, then additional feedback and rewardmechanisms are necessary.

Prior art methods or systems that attempt temporally effective rewardmechanisms include data tracking websites or websites associated withpersonal biometric devices. The data feedback on such sites is oftenfocused on a single metric, which is narrow and minimally informative.

Weight-loss support group sites have a marginally better feedback ratiofor posted comments or messages; users can receive several replies foreach message. The relationship between the feedback/reward and theuser's overall goal in these cases, however, is marginalized. If theuser's overall goal is to lose weight, for example, how direct of areward to that effort is this feedback? The reward of support messagesis more closely related to the behavior of message exchanging itself,and only tangentially related to losing weight. It is a step removedfrom the efforts and behaviors of actually losing weight.

A user needs a personal connection or meaning to the feedback/reward tobe effective. Too often, user profiling is not sufficiently varied orpersonalized. Meaningful feedback, therefore, is limited and contributesto low effort-to-reward feedback ratios.

In existing systems, the desired goal is often a number, a fixedmeasurement, of what is considered healthy for someone with the user'sattributes. This number, this goal measurement, is historically a verypoor motivator. People have been told what they are supposed to weighmany times already. Familiarity with a number is not the same as arelationship or meaning.

SUMMARY OF THE INVENTION

What is needed is a new set of assessment metrics that are fresh,motivating, and meaningful. The present invention provides methods andsystems of motivation and behavior management that provides a user witha novel assessment with an effort-to-reward mechanism that is (1)temporal, (2) tangible, (3) personally meaningful, and (4) has a muchgreater feedback ratio that is far more effective than existingweight-loss, fitness and lifestyle programs.

To enable effective health, fitness and lifestyle behavior management, asoftware and hardware system has been developed that provides immediate,meaningful and engaging feedback for physical and behavioral metrics byproviding a dynamic assessment of these metrics via a high feedbackratio interface. The system simultaneously meets the requirements of allfour effort-to-reward feedback mechanisms—temporal, association,assimilation, and ratio—of an effective behavior management tool.

The hardware and software system is designed to optimize datacollection, organization and display. Hardware components includeintegrated biometric devices, such as scales, that make data collectionautomatic and comprehensive. Data is stored and organized on computerservers. User assessments and data display are conveniently accessiblefrom Internet-enabled devices.

A powerful system of metrics and filters allows for a simultaneouslybroad and deep user assessment spectrum. Motivational and obstacleprofile typing provide a greater variety of data nodes in member recordscreating flexibility. New assessment metrics, including positions andrankings, utilize dynamic reference data sets that can be filtered tomore and more closely resemble any particular user. User interactivitywith the data enriches the user experience and provides more meaningfuldata feedback, and is a key to the effort-to-reward mechanism. Feedbackbased on cross referencing various metrics simultaneously can assist inusers refining their behaviors to be more effective.

Users complete their profile by defining their goal, exercise andnutrition schedule, motivational and obstacle data, and other systempreferences. Each of these data points is an additional data node fororganizing feedback. Upon completing their profile, users record theiractivities on a daily basis and their physical measurementsperiodically. From time to time, users may participate in health andfitness challenges, competitions or other data organizational schemes.Physical measurements may be recorded manually or automatically via anintegrated biometric device. Immediately following data entry, usersaccess one of several dynamic high feedback ratio interfaces. Theseinterfaces allow the user to obtain an assessment of physical metrics,such as weight and body fat percentage, or behavioral metrics, such aslogin frequency and mood. A variety of metric assessments are available.Assessment feedback is dynamic, in that, the active reference data setchanges with overall system usage in nearly live terms.

Rankings and position assessments offer viscerally understood answers to“how am I doing?” questions. Via various screens, users can be ranked orpositioned, on a percentile scale of 1-100, against other profiles inthe active reference data set. The active reference data set isflexible; it can be filtered at the user's whim in real time.

The dynamic and flexible ranking and position assessments featuressatisfy the criteria for an effective behavior management system:

-   -   Temporal Assessment feedback rewards immediately follow user        data entry.    -   Association The behavior of entering data and data assessment        feedback are directly related. Users, in effect, take a        “BodySpex measurement” to find out how they're doing.    -   Assimilation Ranking and positions on a scale of 1-100 are        innately easy to grasp. Filtering allows for meaningful        reference data sets.    -   Ratio Multiple metrics and filters options provide users with a        feedback interface that is very high-ratio.

This system is a positive feedback loop. The very act of accessing thedatabase to see a user's rank and/or position adds more data to thedatabase. A user enters his or her data to find out where he/she ranks,thus increasing the data pool for the next user. The increased data poolis more informative, more valuable, and encourages the next user to seewhere he or she ranks.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and not limitedin the accompanying figures in which:

FIG. 1 a shows an illustrative conceptual diagram of a behaviormanagement system. Between a user's goal desire and goal achievement isthe user's behaviors over time. A behavior management system utilizessoftware to define the goal and metrics to determine progress, tocollect user data of these metrics including behavioral metrics, and toprovide a meaningful assessment, so that the user may refine and improvebehaviors. The cycle continues until the goal is achieved.

FIG. 1 shows a block diagram of components of a hardware and softwarebehavioral management system. Users are connected to the behaviormanagement software via hardware and a network. Hardware includesInternet-enabled devices, professional and consumer biometric deviceswith bidirectional integration and third party professional and consumerbiometric devices with unidirectional integration.

FIG. 2 shows a flow diagram of data types in a hardware and softwarebehavioral management system. User generated data, biometric hardwaredevice generated data, and software generated data flow over a network.

FIG. 3 shows a flow diagram of data between various components of ahardware and software behavioral management system. Data flows from andto users via Internet-enabled devices, professional and consumerbiometric devices with bidirectional integration and third partyprofessional and consumer biometric devices with unidirectionalintegration. Each of these data streams connects with the BodySpexservers via a network. Additional third party assimilated data flows tothe servers directly or via a network.

FIG. 4 shows a block diagram of the System Architecture, whichillustrates the relationships between users, biometric devices, thewebsite, web services, and the database.

FIG. 5 shows a schematic and data flowchart for the website. Users join,and then set up their user record, optionally by completing a gettingstarted sequence. User records are maintained and updated via variousdata entry screens and functions. All user record data is stored in anintelligent reservoir on the servers, where it is organized and relatedwith other data, such as, assimilated data, internal process and systemdata, exercise, gear, tools, and forum data. Data is displayed for theuser via their MySpex page, support features and high feedback ratiointerfaces.

FIG. 6 a shows an exemplary webpage for a user defining their goal inthe getting started sequence. Users define their goal, assign theirmetric and target measure measurement. This goal is related to personalgoal reasons and goal rewards creating additional data nodes forfeedback.

FIG. 6 b shows an exemplary webpage for a user scheduling their exercisein the getting started sequence. Users assign each day of the week forrest or exercise. For exercise days, the user declares how many minuteshe/she plans to engage in some form of exercise. In some embodiments,the user can select from a menu of specific exercises or fully definedexercise plans. These are additional data nodes for feedback.

FIG. 6 c shows an exemplary webpage for a user defining theirnutritional and other behavioral tracking in the getting startedsequence. Users select any number of additional behaviors to track.These are additional data nodes for feedback.

FIG. 6 d shows an exemplary webpage for a user completing theirmotivational profile in the getting started sequence. A user ispresented with four questions with an A or B answer which most closelyreflects their motivational profile. This feature creates sixteendistinct motivational profiles and each user is flagged for one and onlyone. This is an additional data node for feedback.

FIG. 6 e shows an exemplary webpage for a user completing their obstacleprofile in the getting started sequence. A user is presented with a listof obstacle statements which are selected as applicable to reflect theuser's historical obstacles to achieving their goal. This feature isorganized to create sixteen distinct obstacle profiles and each user isflagged for one and only one. This is an additional data node forfeedback.

FIG. 6 f shows an exemplary webpage for a user completing their alertand reminder settings in the getting started sequence. Users selectunder what circumstances they want system alert and reminder prompts viaemail. In addition to system logic, selections by the user areadditional data nodes for feedback.

FIG. 7 shows a diagram of how user data is accessible and flexible viathe interactive chart. User records include all personal physical andbehavioral measurements as well as other data typing used for filters.All user records are stored and organized together and can be accessedvia the feedback interfaces to find measurement data counts given anycombination of filters.

FIG. 8 shows an exemplary webpage of the high feedback ratio interface.Users select a metric, then filters as desired. A chart or graph orother data display type is automatically generated. In this case, ahistogram chart of male weight is displayed with a member count on the‘y’ axis and number of pounds on the ‘x’ axis. User rank or position, asapplicable, is displayed along with other pertinent information aboutthe active reference data set.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 a illustrates the conceptual architecture of an effectivehardware and software behavior management system. Between a user's goaldesire and goal achievement is the user's behavior cycle. User behaviorsare parsed into a set of metrics that can be measured to determineprogress. User measurements, including both physical and behavioraldata, with respect to these metrics are stored on servers. Data can bemanually entered, captured via integrated biometric hardware devices orgenerated by software system processes. User data is organized to enablethe display of meaningful and engaging assessment feedback. The presenteffective behavior management system provides assessment feedback thatmeets the requirements of all four effort-to-reward mechanisms—temporal,association, assimilation, and ratio—of an effective behavior managementtool. A user that is properly motivated and informed refines his/herbehavior and continues this cycle until the goal is achieved.

FIG. 1 diagrams the components of a hardware and software behavioralmanagement system. Users interact with hardware, including but notlimited to Internet-enabled devices, professional and consumer biometricdevices with bidirectional integration and third party professional andconsumer biometric devices with unidirectional integration. Such devicesinclude, for example, body composition scales, pedometers, and heartrate monitors. These devices are connected with the system servers via anetwork and the behavior management software which resides there.

In one embodiment, the device comprises a body composition scale orkiosk. The fitness kiosk is a self-serve apparatus that features thefollowing components in a powder-coated steel housing: body compositionscale, internet-enabled CPU, video-enable touch screen monitor,speakers, thermal printer, an optional bill acceptor, a power supply,internet card, fuses and electrical chassis. The graphic display andauditory prompts from the speakers guide a user through a bodycomposition test. Proprietary software, running on the CPU, integratesthe scale and supporting devices from the individual control standpointas well as in terms of the overall test sequence logic.

Test data from the kiosk is automatically sent to private user accountsonline. If the local network is down for some reason, results are cachedlocally then uploaded when access is restored. Users can createindividual accounts either on the kiosk or the website, and this,together with how the kiosk is used, is explained in more detail below.

FIG. 2 illustrates the different types of data used and generated by thesystem. Biometric data includes, but is not limited to, weight, body fatpercentage, height, age, blood pressure readings, injury status, milesrun, calories consumed, and nutritional intake. Behavioral dataincludes, but is not limited to, user login frequency, recordingactivity percentage, amount of exercise, intensity of exercise, type ofexercise, and time of day meal eaten. Expression data includes, but isnot limited to, expressions of opinions, preferences, feelings, moods,energy level, comments, and diary entries. Derivative data includes, butis not limited to, data derived from other types of data and/or analysisof other data, such as weight loss to date which is a subtraction ofweight data from two different dates. Derivative data also includes dataderived from simultaneously cross referencing various metrics. Internalsystem data includes, but is not limited to, data or flags linking orrelating varying types of data together. Assimilated data includes, butis not limited to, data from outside databases which may or may notinvolve types of data mentioned. Internal process data includes, but isnot limited to, obstacle and motivational type definitions, data-miningformulas, algorithms and functions. Users generate biometric, behavioraland expression data. Biometric hardware devices generate biometric andbehavioral data. System software generates derivative and internalsystem data and utilizes internal process data.

The flow of data between the system components is shown in FIG. 3. Usersenter data into the system via Internet-enabled devices, such ascomputers and smart phones, and via professional and consumer biometricdevices with bidirectional integration, and via third party professionaland consumer biometric devices with unidirectional integration. Usersmay receive or view data from the system via Internet-enabled devices,such as computers and smart phones, and via professional and consumerbiometric devices with bidirectional integration. Internet-enableddevices and profession and consumer biometric devices with bidirectionalintegration send data to and receive data from the servers via anetwork. Third party professional and consumer biometric devices withunidirectional integration send data to the servers via a network, whileassimilated third party databases send data to the servers via a networkor directly.

FIG. 4 shows the system architecture. Data is organized and stored inthe database. Website software is linked to the database and the websiteis accessed by users via a network. Web services software is linked tothe database and communicates with bio-metric devices via a network.

FIG. 5 shows a schematic and data flowchart for the website component ofa hardware and software behavior management system. The design of thewebsite clusters around three essential functions: data collection, dataorganization, and data display.

In general, a user's initial interaction with the system will be via thewebsite directly or a biometric measurement test on an integrated deviceor system. From one of these entry points, a user is presented with datafeedback in the form of a Results Page. After viewing the test resultsand the assessment, the user will be prompted to join. The join page isa typical website form where basic account information, such as name,gender, birth date, time zone, postal code, is gathered to create aunique user profile.

Upon validating their email address by clicking a link embedded in anautomatically generated email response to their join form data, usersmay optionally complete a Getting Started Sequence. The Getting StartedSequence is a series of form and data collection pages to complete theirUser Record. In this sequence, users define a goal, includingappropriate metric for measuring progress, schedule exercises, schedulenutrition and tracking items, select motivation responses, selectobstacle responses, and choose support settings.

A User Record is comprised of user profile and biometric data collectedas noted above, as well as other data, such as behavioral data,expression data, derivative data, system data and process data withineach user's record. A User Record is regularly updated through variousprocesses, which alter and add to the data within the User Record,including derivative data, system data and process data.

Various pages are provided for the ongoing maintenance and data entry ofthe user's health, fitness and lifestyle. These include measurementswhere periodic biometric data is recorded, as well as: Daily Log—wheredaily expression and behavioral data is recorded; Meal Diary—where dailyexpression and behavioral data is recorded; Schedule—where certainbehavioral data is managed; and, MyAccount—where Profile data ismanaged; Challenges—where user interaction is characterized as a healthand/or fitness competition, and resulting data records create anadditional set of data nodes for feedback.

The present software system organizes data in a manner which enableshigh feedback ratio interfaces. Just as each individual User Record isstored, so too is an appropriate aggregate record of all records. Alarge, flexible matrix encoded with each individual User Record, as wellas an aggregate record of all records, enable users to filter thereference data set and relate their specific record against a referencedata set of their choice. In addition to all user records, data in thereservoir includes Assimilated Data, such as a third party database, aswell as additional internal process data, additional internal systemdata, and exercise, gear, tools and forum databases. Each of these addsdata nodes to the matrix and additional potential record relationships.

Several pages are dedicated to data display. MySpex is an overview.MySupport is a message center. MyGraphs display a history of user dataand records in numerical and/or graphic form. And the key data displayfeature is the high feedback ratio interfaces where users select ametric, then filter as desired to receive measurement and behavior rankand/or position assessments and other feedback.

FIG. 5 a shows an exemplary Results Page. Test results, in this caseshowing the results of a full test from an integrated fitness kiosk(weight, body fat %, metabolism, BMI, lean mass and fat mass), aredisplayed with a date. A large histogram chart displays the defaultmeasurement, in this case, weight. Below the chart is useful informationthat shows the user's percentile in the current data set. Otherinformation that can be provided includes (1) a Median Position, wherehalf the users are more than and half are less than the user's position;and (2) Target positions, where results one or two positions better thanthe user's current position are provided.

Users can interact with their results and the feedback display. Usersfirst select a metric. The next step is to select a data set time frame,such as, all-time, 30 days, 7 days, or today. With these selected, thesystem generates a chart, graph or other data display type depending onthe data selection. In this case, a histogram chart of female weight isdisplayed with a member count on the ‘y’ axis and number of pounds onthe ‘x’ axis. The chart indicates where the user is positioned for thecurrent data set. The legend describes the current data set.Additionally, users can reference assessments or data generated throughsimultaneous cross referencing of multiple metrics.

A Filter Panel allows the user to filter the data set based on apre-determined list of additional data nodes. In this example, the usercan filter by gender, age, height and body type. The user can select anycombination of filters. Selecting any filter alters the active referencedata set and the accompanying chart responds accordingly. Altering theactive reference data set affects the user's position in the datadisplay. Position or Rank provides the user with a percentile position1-100, which can be very motivating to the user, encouraging him or herto improve position or rank. Other valuable information that is providedcan include for example, (1) a Median Position, where half the users aremore and half are less than the user's position; and (2) Targetpositions, where results one or two positions better than the user'scurrent position are provided.

Links to additional information can also be provided. For user's whohave not fully registered on the site, there are links to join and theirtest data will be saved to their account.

FIG. 6 a shows the first stage of the Getting Started Sequence: DefineYour Goal. A drop down list provides a set of pre-defined goals, such asLose Weight or Drop Clothing Size, or an option to define your own. Uponselecting a goal, a Target Metric Field displays where the user enterstheir target measurement based on the type of goal selected. Forexample, if Lose Weight was selected, the measurement metric is pounds(or kilograms) and the user enters their Target Weight in pounds (orkilograms). Measurement metrics can be pounds, percentage, time,distance, size, inches etc., anything health, fitness, diet, orlifestyle related. For pre-defined goals, the goal and the metric dataare fully integrated into the software system enabling each as a datanode for feedback.

Next, a drop down list provides a set of pre-defined Goal Reasons and acomment field to enter a personalized text entry. Users may also definetheir own reason if the list does not suit them. For pre-defined GoalReasons, the user's choice provides another data node. Comments arestored and can be “driven back” to the user in emails or messages uponthe occurrence of certain situations to help the user stay motivated.

Next, a drop down list provides a set of pre-defined Goal Rewards and acomment field to enter a personalized text entry. Users may also definetheir own reward if the list does not suit them. For pre-defined GoalRewards, the user's choice provides another data node for feedback.Comments are stored and can be “driven back” to the user in emails ormessages upon the occurrence of certain situations to help the user staymotivated.

FIG. 6 b shows an exemplary webpage for a user scheduling their exercisein the Getting Started Sequence. A week-long calendar view enables theuser to assign their intended amount of exercise on each day of theweek. This can be a repeating one-week schedule, a multi-week schedule,a monthly schedule, a daily schedule, any variation thereof, or anycalendar view that is desired.

Users select whether the day of the week is a “rest” day or an“exercise” day. For each exercise day selected, the user chooses from adropdown list how long they intend to exercise that day, i.e. 20minutes, 45 minutes, etc. The total amount of time is calculated anddisplayed. Each of these choices, which days are rest or exercises,number of rest days, number of exercise days, amount of exercise on anyand all days, total exercise time, etc. are additional data nodes forfeedback. The exercise can be any activity that falls within thedescription of “exercise.” Alternatively, specific exercises can beselected and scheduled rather than simply the generic “exercise.”“Exercise” can be further defined in the system as a strength exerciseor a cardiovascular exercise. Individually defined exercises, exerciseroutines, all-in-one exercise programs, etc. can also be used. Datanodes can also include such information as, for example, weight lifted,repetitions, sets, interval rest, intensity, minutes, etc.

FIG. 6 c shows an exemplary webpage for a user defining theirnutritional and other behavioral tracking in the Getting StartedSequence. Users select from a pre-defined list of items to track on adaily basis. Examples include a Meal Diary with meal names and times;calories, fat grams, protein grams, carbohydrate grams, glasses ofwater, hours of sleep, and treats. These items are selected via acheckbox, and are appropriately flagged as such in the User's Record.Users can use the default desired target amount of daily tracked items(for example, 8 hours of sleep, 10 glasses of water) or define a customamount. For pre-defined Track Items, the user's data provides anothernode for feedback.

FIG. 6 d shows the fourth stage of the Getting Started Sequence, anexemplary webpage for a user completing their motivation profile. Usersare presented with questions relating to motivation and are asked toindicate an A or B response for each question which most closelydescribes how they feel about the question. This feature creates sixteendistinct motivational profiles and each user is flagged for one and onlyone profile. This is an additional data node for feedback. The purposeis to identify and group users based on various data nodes and determinepatterns and expectations based on this data to better guide and directuser's toward increased desired behaviors and goal achievement.

FIG. 6 e shows the fifth stage of the Getting Started Sequence, anexemplary webpage for a user completing their obstacle profile. Usersare presented with a series of checkboxes, each associated with anobstacle statement. Users indicate for each obstacle whether it hascontributed to the user failing to achieve a similar goal in the past.The obstacles statements are organized in the software to form fourobstacle groups: social, information, constitution, injury. This featureis organized to create sixteen distinct obstacle profiles and each useris flagged for one and only one obstacle type. This is an additionaldata node for feedback. The purpose is to identify and group users basedon various data nodes and determine patterns and expectations based onthis data to better guide and direct user's toward increased desiredbehaviors and goal achievement.

FIG. 6 f shows the fifth stage of the Getting Started Sequence, anexemplary webpage for a user completing their alert and remindersettings. Users set their alert and reminders preferences via thispanel. Users select checkboxes for the types of email alerts andreminders they want the software to send. In addition to system logic,selections by the user are additional data nodes for feedback.

Upon completing their Getting Started Sequence, a user is fullyregistered. A user's MySpex page is their private account home page, adashboard of sorts, where their data is summarized: a calendar viewsummaries their upcoming scheduled activities, a summary of theirposition and rankings for various metrics, and a status graph of theirgoal progress.

FIG. 7 shows how data is organized and made accessible. All user datarecords are stored in the main database, and stored in a manner thatallows for culling data in a variety of ways. A summary of all recordsthat meet certain criteria are available for parsing. Users selectmeasurement, time frame, and check filter boxes on the variousInteractive Charts. This pulls up a variable dynamic (live) data set andis displayed in a variety of methods.

All measurements (1) are stored and keyed with other data that allowsfor filtering of that data set. Selecting a Filter (1) returns onlythose measurements that meet the criteria, that is, a subset of thewhole initial data set. Further, selecting Filters (1 and 2) returnsonly those measurements that meet the criteria for 1 and 2. Users mayalso select only 2, for example, and the entire Measurement 1 (M1) dataset will return a smaller data set that meets M1 and F2 criteria. Inthis way, any combination of filters and a measurement, and timeframedata set, is available. In this example, M1 is filtered by F1, F2, andF3, each subset of the group above.

The user's position and/or rank are determined by the user's currentmeasurement within the active data set. As the data set is changed, theuser's position will change, as will the median position/rank. Otherranks will change as well.

A projected daily routine for a user includes logging in. Then, they goto their Daily Log page to record their day's activities. Upon loggingthe day's activities from a pre-populated list generated by theirschedule, they can review their new positions and rankings on theirbehavioral results page and interact with the latest data sets. Aseparate Meal Diary functions the same way.

Periodically, users will be prompted to their measurements page toupdate their measurements. Integrated devices will update this dataautomatically. Upon entering new data, users can review their newpositions and rankings on their measurements Results Page and interactwith the latest data sets.

Ideally, upon interacting with the various Results Pages, users willrefine their exercise and meal schedules to move toward an everincreasing effectiveness toward reaching their goals. Users can refinetheir behaviors based upon the results and assessments obtained fromsimultaneously cross referencing various metrics within the system.

Additional behaviors that users are encouraged to participate in on thesite are reading articles and comments in the public forums. They canbrowse an exercise library to find new exercises to incorporate intotheir schedule. They can receive and send support via emails andinternal messaging from their friends list or group. They can join achallenge to compete with other users. They can maintain a diary, orblog. Other community features can include an events calendar forexercise and fitness events.

FIG. 8 shows an exemplary webpage of a high feedback ratio interface.Users first select a metric. The second step is to select data set timeframe, such as, all-time, 30 days, 7 days, or today. With theseselected, the system generates a chart, graph or other data display typedepending on the data selection. In this case, a histogram chart of maleweight is displayed with a member count on the ‘y’ axis and number ofpounds on the ‘x’ axis. The chart indicates where the user is positionedfor the current data set. The legend describes the current data set.

A Filter Panel allows the user to filter the data set based on apre-determined list of additional data nodes. In this example, the usercan filter by gender, age, and height. The user can select anycombination of filters. Selecting any filter alters the active referencedata set and the accompanying chart responds accordingly. Altering theactive reference data set affects the user's position in the datadisplay. Position or Rank provides the user with a percentile position1-100, which can be very motivating to the user, encouraging him or herto improve position or rank.

Other valuable information that is provided can include (1) a MedianPosition, where half the users are more and half are less than theuser's position; and (2) Target positions, where one or two positionsbetter than the user's current position are provided.

The focus of the feature is to encourage the user's engagement withtheir measurements. They can select a data set that can more and moreclosely resemble their attributes. Users will “play” with the tool tosee where they are and how they're doing with respect to others anddetermine which behavioral variations are producing the best results.Users who are thus engaged in their measurements are more inclined toimprove them.

The system and methods described above fulfill four requirements of aneffective behavior management tool—that is, (1) temporal, (2) tangible,(3) personally meaningful, and (4) a high feedback ratio.

Example 1

Amy, 36 years old, joins a health club to lose fifteen pounds. She has asummer vacation planned with friends she hasn't seen in five years andwants to look good in her bathing suit. At the club, Amy notices a newBodySpex scale. The video touch screen announces free weight and bodyfat percentage test results, so she steps up to give it a try.

Touching the screen, Amy is presented with a Welcome screen. On thisscreen, Amy is offered the option of a free test, where results areemailed to the user, or a test with immediate results available for $2.Amy presses the free test button.

A Login screen appears for Amy to enter her email address or nickname,if she were already a BodySpex member. Amy taps out her email addressvia the onscreen keyboard. Next is a Password screen. Amy thinks of apassword she can easily remember and enters it.

Amy is now presented with a screen that offers two different tests: abody fat test and a weight-only test. She notes that the body fat testmust be taken in bare feet, and reads a caution that she should not haveany internal electrical devices, such as a pacemaker. Determined tolearn her body fat percentage, Amy selects BodyFat Test.

Amy is presented with a series of screens to collect necessary profileinformation for an accurate body fat test via bioelectric impedance, theunderlying technology of the scale. First is a Gender screen. Amyselects the image of a woman. On the next screen, Amy enters her height,5′6″. Amy enters her birth date: Jul. 4, 1972 on the next screen. Amy isthen presented a screen with six different body types, varying from amuscular female bodybuilder to an overweight woman. Amy selects theimage that most closely resembles her body type, slightly overweight. Onthe next screen, Amy is given the option to enter her desired weightgoal. Amy uses the onscreen keypad to enter 145 lbs. Next, Amy isprompted to select an image which most closely resembles how manyclothes she is wearing. Amy reads on an information popup that the scaleautomatically deducts the weight of clothes to get a more accuratereading. Amy selects the image in shorts and tank-top. The scale willautomatically deduct 1.2 pounds from her weight.

The scale is prepared for Amy's test and Amy takes off her shoes andsocks. The scale prompts Amy to step on the scale and she does. Shestands still for about 15 seconds and the test is complete. The scaledisplays a message telling Amy to check her email for test results. Thewhole process has taken less than two minutes. Amy puts on her shoes andsocks and does her workout.

When Amy gets home, she checks her email. There is an email fromBodySpex with a few kind words and a link to her results. Amy clicks thelink in her email. Embedded into this link is a unique identifier,enabling the BodySpex system to display Amy's results specifically andprivately for her.

A browser is opened and Amy is automatically directed to the scaleresults page on the BodySpex website where she can read her testresults: Weight 160 lbs, BodyFat 33.1%, Metabolism 1245 kcals, BMI 26.3,Lean Mass 107 lbs, Fat Mass 53 lbs.

In addition to her results, and what really catches Amy's eye, is aninteractive feedback Chart. Right now the Chart is showing a graph of alopsided bell curve with a little flag indicating her current weight of160 lbs. The Chart legend reads Members 9,856 and Gender: Female. Belowthe Chart is more information. It indicates her Weight position is 57and that 5,617 members have a lower value while 4,238 members have ahigher value. Amy is in the 57^(th) percentile for this reference group.

Amy sees a drop down list that currently reads ‘weight’, but has optionsfor all of the metrics provided by the BodySpex scale test: weight,bodyfat %, metabolism, BMI, LeanMass, and FatMass. Below this is aseries of check boxes under a title that reads “Compare To”. Thecheckbox for My Gender is checked. Others, like My Age, My Height arenot checked. Amy checks the box for My Age.

The chart immediately changes to reflect a new active reference data.The chart legend now reads Members: 1,234, Gender Female, Age 35-37.Amy's position on the chart has changed and so has her positioninformation below the chart. Her rank for this data reference set hasimproved to 48. Amy rightly concludes that for women her age, she'sbetter than the median.

Excited to see how she measures up against all the possible variablesoffered with this chart and her one test, she spends ten minutesselecting each of the metrics and each combination of filters for each.

Amy discovers there are 100 members who match her profile closely:Female, 35-37 years old, 5′5″-5′7′ tall, and workout at her club. Amy'sranked 51 and that doesn't sit well with her. She's highly motivated toget in the top 25, and can't wait to get back to the gym.

Amy notes that becoming a BodySpex.com member is free and members enjoymany more metrics and filters on their interactive feedback charts. Amypromptly clicks the join button, where her scale data will beautomatically imported to her new web account. Amy plans to take anotherscale test at her club in a week.

It is to be recognized that depending on the embodiment, certain acts orevents of any of the methods described herein can be performed in adifferent sequence, may be added, merged, or left out all together(e.g., not all described acts or events are necessary for the practiceof the method). Moreover, in certain embodiments, acts or events may beperformed concurrently, e.g., through multi-threaded processing,interrupt processing, or multiple processors, rather than sequentially.

Those of skill in the art will recognize that the various illustrativelogical blocks and algorithm steps described in connection with theembodiments disclosed herein may be implemented as electronic hardware,software stored on a computer readable medium and executable by aprocessor, or combinations of both. Whether such functionality isimplemented as hardware or software depends upon the particularapplication and design constraints imposed on the overall system.Skilled artisans may implement the described functionality in varyingways for each particular application, but such implementation decisionsshould not be interpreted as causing a departure from the scope of thepresent invention.

The various illustrative logical blocks, modules, and circuits describedin connection with the embodiments disclosed herein may be implementedor performed with a general purpose processor, a digital signalprocessor (DSP), an application specific integrated circuit (ASIC), afield programmable gate array (FPGA) or other programmable logic device,discrete gate or transistor logic, discrete hardware components, or anycombination thereof designed to perform the functions described herein.A general purpose processor may be a microprocessor, but in thealternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration.

The steps of a method or algorithm described in connection with theembodiments disclosed herein may be embodied directly in hardware, in asoftware module executed by a processor, or in a combination of the two.A software module may reside in RAM memory, flash memory, ROM memory,EPROM memory, EEPROM memory, registers, hard disk, a removable disk, aCD-ROM, or any other form of storage medium known in the art. Anexemplary storage medium is coupled to the processor such the processorcan read information from, and write information to, the storage medium.In the alternative, the storage medium may be integral to the processor.The processor and the storage medium may reside in an ASIC.

Various modifications to these examples may be readily apparent to thoseskilled in the art, and the principles defined herein may be applied toother examples without departing from the spirit or scope of the novelaspects described herein. Thus, the scope of the disclosure is notintended to be limited to the examples shown herein but is to beaccorded the widest scope consistent with the principles and novelfeatures disclosed herein.

1. A behavioral management system comprising: software residing on aserver and hardware connected to the server via a network, wherein usergenerated data is entered into the system and organized and stored in adatabase in a manner that enables high feedback ratio interfaces, suchthat a user is provided with a position and/or rank determined bycomparing an individual user's current data to an active data set. 2.The system of claim 1, wherein the hardware is selected from the groupconsisting of an Internet-enabled device, a biometric device withbidirectional integration, and a biometric device with unidirectionalintegration.
 3. The system of claim 1, wherein the hardware is selectedfrom the group consisting of a body weight scale, a body compositionscale, a pedometer and a heart rate monitor.
 4. The system of claim 1,wherein the user generated data is of a type selected from the groupconsisting of biometric data, behavioral data, and expression data. 5.The system of claim 4, wherein the biometric data is selected from thegroup consisting of weight, body fat percentage, height, age, bloodpressure reading, injury status, miles run, calories consumed andnutritional intake.
 6. The system of claim 4, wherein the behavioraldata is selected from the group consisting of user login frequency,recording activity percentage, amount of exercise, intensity ofexercise, type of exercise and time of day meal eaten.
 7. The system ofclaim 4, wherein the expression data is selected from the groupconsisting of opinions, preferences, feelings, moods, energy level,comments and diary entries.
 8. The system of claim 4, wherein theexpression data is selected from the group consisting of auser-generated motivation profile or a user-generated obstacle profile.9. The system of claim 1, wherein the high feedback ratio interfaceallows the user to reference additional data generated throughsimultaneous cross-referencing of multiple metrics.
 10. The system ofclaim 1, wherein the user can select a combination of filters to alterthe active data set, thereby affecting the user's position and/or rank.11. A behavioral management system comprising a body composition scalehaving an Internet-enabled CPU and software running on the CPU, whereinindividual test data obtained from the scale is organized and stored ina database, and wherein the system allows individual users to relatetheir individual test data against a reference data set which comprisesan aggregate record of all individual test data, such that a user isprovided with a position and/or rank within that reference data set. 12.The system of claim 11, wherein the system further comprises a highfeedback ratio interface that allows the user to reference additionaldata generated through simultaneous cross-referencing of multiplemetrics.
 13. The system of claim 11, wherein the user can select one ormore filters to alter the reference data set, thereby affecting therelationship between the individual test data and the reference dataset, resulting in a different position and/or rank within the alteredreference data set.
 14. The system of claim 11, wherein the individualtest data is body weight.
 15. The system of claim 11, wherein theindividual test data is body fat percentage.
 16. The system of claim 13,wherein the filter is selected from the group consisting of gender,height, and age.